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Abstract-We propose a metric for comparing the anthropomorphic motion capability of robotic and prosthetic hands. The metric is based on the evaluation of how many different postures or configurations a hand can perform by studying the reachable set of fingertip poses. To define a benchmark for comparison, we first generate data with human subjects based on an extensive grasp taxonomy. We then develop a methodology for comparison using generative, nonlinear dimensionality reduction techniques. We assess the performance of different hands with respect to the human hand and with respect to each other. The method can be used to compare other types of kinematic structures.

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Errors up to +/- 30 mm in determining the COP with piezoelectric force plates have been reported in the literature. To compensate for these errors, correction formulas were proposed, based on measurements with single point loads. In this paper, it will be shown that the errors in the COP depend on the load distribution. Two examples are presented: (1) simulated balance study, and (2) different pressure patterns during walking. Accurate corrections can only be made for forces distributed over a small area. Errors are expected to be overcompensated if there are only a few pressure peaks separated by large distances. These errors can be as large as the statistical errors (5.8 +/- 3.7 mm) after compensation. For certain situations, it is probably better not to use correction formulas.

The interpretation of joint kinematics data in terms of displacements is a product of the type of movement, the measurement technique and the underlying model of the joint implemented in optimization procedures. Kinematic constraints reducing the number of degrees of freedom (DOFs) are expected to compensate for measurement errors and noise, thus, increasing the reproducibility of joint angles. One approach already successfully applied by several groups approximates the healthy human knee joint as a compound hinge joint with minimal varus/valgus rotation. Most of these optimizations involve an orthogonality constraint. This contribution compares the effect of a model with and without orthogonality constraint on the obtained joint rotation angles. For this purpose, knee joint motion is simulated to generate kinematic data without noise and with normally distributed noise of varying size. For small noise the unconstrained model provides more accurate results, whereas for larger noise this is the case for the constrained model. This can be attributed to the shape of the objective function of the unconstrained model near its minimum.

Complete agreement was found between the results of the presented calculations and our own clinical experience in removed DHSs.

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